This function calculates topological overlap of a small set of vectors with respect to a whole data set.
vectorTOM(
datExpr,
vect,
subtract1 = FALSE,
blockSize = 2000,
corFnc = "cor", corOptions = "use = 'p'",
networkType = "unsigned",
power = 6,
verbose = 1, indent = 0)a data frame containing the expression data of the whole set, with rows corresponding to samples and columns to genes.
a single vector or a matrix-like object containing vectors whose topological overlap is to be calculated.
logical: should calculation be corrected for self-correlation? Set this to
TRUE if vect contains a subset of datExpr.
maximum block size for correlation calculations. Only important if vect
contains a large number of columns.
character string giving the correlation function to be used for the adjacency
calculation. Recommended choices are "cor" and "bicor", but other functions can be used as
well.
character string giving further options to be passed to the correlation function.
character string giving network type. Allowed values are (unique abbreviations of)
"unsigned", "signed", "signed hybrid". See adjacency.
soft-thresholding power for network construction.
integer level of verbosity. Zero means silent, higher values make the output progressively more and more verbose.
indentation for diagnostic messages. Zero means no indentation, each unit adds two spaces.
A matrix of dimensions n*n, where n is the number of columns in vect.
Topological overlap can be viewed as the normalized count of shared neighbors encoded in an adjacency
matrix. In this case, the adjacency matrix is calculated between the columns of vect and
datExpr and the topological overlap of vectors in vect measures the number of shared
neighbors in datExpr that vectors of vect share.
Bin Zhang and Steve Horvath (2005) "A General Framework for Weighted Gene Co-Expression Network Analysis", Statistical Applications in Genetics and Molecular Biology: Vol. 4: No. 1, Article 17
TOMsimilarity for standard calculation of topological overlap.